Hybrid Prediction-Driven High-Throughput Sustainability Screening for Advancing Waste-to-Dimethyl Ether Valorization.

Assessing the prospective climate preservation potential of novel, innovative, but immature chemical production techniques is limited by the high number of process synthesis options and the lack of reliable, high-throughput quantitative sustainability pre-screening methods. This study presents the sequential use of data-driven hybrid prediction (ANN-RSM-DOM) to streamline waste-to-dimethyl ether (DME) upcycling using a set of sustainability criteria. Artificial neural networks (ANNs) are developed to generate in silico waste valorization experimental results and ex-ante model the operating space of biorefineries applying the organic fraction of municipal solid waste (OFMSW) and sewage sludge (SS). Aspen Plus process flowsheeting and ANN simulations are postprocessed using the response surface methodology (RSM) and desirability optimization method (DOM) to improve the in-depth mechanistic understanding of environmental systems and identify the most benign configurations. The hybrid prediction highlights the importance of targeted waste selection based on elemental composition and the need to design waste-specific DME synthesis to improve techno-economic and environmental performances. The developed framework reveals plant configurations with concurrent climate benefits (-1.241 and -2.128 kg CO2-eq (kg DME)-1) and low DME production costs (0.382 and 0.492 € (kg DME)-1) using OFMSW and SS feedstocks. Overall, the multi-scale explorative hybrid prediction facilitates early stage process synthesis, assists in the design of block units with nonlinear characteristics, resolves the simultaneous analysis of qualitative and quantitative variables, and enables the high-throughput sustainability screening of low technological readiness level processes.

A rapid removal of Phaeocystis globosa from seawater by peroxymonosulfate enhanced cellulose nanocrystals coagulation.

Cellulose nanocrystals (CNC) are recognized as promising bio-based flocculants for controlling harmful algal blooms (HABs). Due to the charge shielding effect in seawater and the strong mobility of algae cells, CNC can't effectively remove Phaeocystis globosa from seawater. To solve this problem, peroxymonosulfate (PMS) was used to enhance the coagulation of CNC for rapidly removal of P. globosa. The results showed that 91.7% of Chl-a, 95.2% of OD680, and 97.2% of turbidity of P. globosa were reduced within 3 h with the use of 200 mg L-1 of CNC and 20 mg L-1 of PMS. The removal of P. globosa was consisted of inactivation and flocculation. Notably, electron paramagnetic resonance (EPR) spectrums and quenching experiments revealed that the inactivation of P. globosa was dominated by PMS oxidation and 1O2. Subsequently, CNC entrained inactivated algal cells to settle to the bottom to achieve efficient removal of P. globosa. The content of total organic carbon (TOC) and chemical oxygen demand (COD) decreased significantly, indicating that a low emission risk of algal cell effluent was produced in the CNC-PMS system. In view of the excellent performance on P. globosa removal, we believe that the CNC-PMS system has great potential for HABs treatments.

Energy-saving COVID-19 biomedical plastic waste treatment using the thermal - Catalytic pyrolysis.

The rate of Biomedical waste generation increases exponentially during infectious diseases, such as the SARS-CoV-2 virus, which burst in December 2019 and spread worldwide in a very short time, causing over 6 M casualties worldwide till May 2022. As per the WHO guidelines, the facemask has been used by every person to prevent the infection of the SARS-CoV-2 virus and discarded as biomedical waste. In the present work, a 3-ply facemask was chosen to be treated using the solvent, which was extracted from the different types of waste plastics through the thermal-catalytic pyrolysis process using a novel catalyst. The facemask was dispersed in the solvent in a heating process, followed by dissolution and precipitation of the facemask in the solvent and by filtration of the solid facemask residue out of the solvent. The effect of peak temperature, heating rate, and type of solvent is observed experimentally, and it found that the facemask was dissolved completely with a clear supernate in the solvent extracted from the (polypropylene + poly-ethylene) plastic also saved energy, while the solvent from ABS plastic was not capable to dissolute the facemask. The potential of the presented approach on the global level is also examined.

Post COVID-19 ENERGY sustainability and carbon emissions neutrality.

This review covers the recent advancements in selected emerging energy sectors, emphasising carbon emission neutrality and energy sustainability in the post-COVID-19 era. It benefited from the latest development reported in the Virtual Special Issue of ENERGY dedicated to the 6th International Conference on Low Carbon Asia and Beyond (ICLCA'20) and the 4th Sustainable Process Integration Laboratory Scientific Conference (SPIL'20). As nations bind together to tackle global climate change, one of the urgent needs is the energy sector's transition from fossil-fuel reliant to a more sustainable carbon-free solution. Recent progress shows that advancement in energy efficiency modelling of components and energy systems has greatly facilitated the development of more complex and efficient energy systems. The scope of energy system modelling can be based on temporal, spatial and technical resolutions. The emergence of novel materials such as MXene, metal-organic framework and flexible phase change materials have shown promising energy conversion efficiency. The integration of the internet of things (IoT) with an energy storage system and renewable energy supplies has led to the development of a smart energy system that effectively connects the power producer and end-users, thereby allowing more efficient management of energy flow and consumption. The future smart energy system has been redefined to include all energy sectors via a cross-sectoral integration approach, paving the way for the greater utilization of renewable energy. This review highlights that energy system efficiency and sustainability can be improved via innovations in smart energy systems, novel energy materials and low carbon technologies. Their impacts on the environment, resource availability and social well-being need to be holistically considered and supported by diverse solutions, in alignment with the sustainable development goal of Affordable and Clean Energy (SDG 7) and other related SDGs (1, 8, 9, 11,13,15 and 17), as put forth by the United Nations.

A graphical approach for mixed ratio optimisation in the binary mixed amine solution.

Chemical absorption method plays an important role in the process of CO2 separation. One major problem for chemical absorption is huge energy consumption, which is affected by the performance of absorbents. Developing a type of absorbent with high absorption capacity and low regenerative energy consumption is a research topic that attracts attention. The combination of two or more amines is one way to develop new solvents. However, the change of amine liquid ratio can cause a series of complex nonlinear changes in absorption capacity, absorption heat, the heat of vaporisation and sensible heat. It is of interest to visualise the amine solution mixing ratio optimisation to help reduce the energy consumption and increase the absorption capacity. Derivative analysis of standardised vs variables diagram (DSVD), a kind of graphical method based on maximum benefit and minimum consumption, is proposed to determine the optimal mixing ratio of binary amine solution. This novel approach helps to visualise what kind of amines are not suitable for compounding, what kind of amines have the best compounding ratio, and how to determine the optimal compounding ratio. The optimal mixing ratio of the Methyldiethanolamine (MDEA) - Piperazine (PZ) system and MDEA - Monoethanolamine (MEA) were optimised by this method. The optimal ratio of MDEA - PZ and MDEA - MEA are 0.6 (PZ: MDEA = 0.6:0.4, wt.%) and 0.8 (MEA: MDEA = 0.8:0.2, wt.%).

Changes in water use and wastewater generation influenced by the COVID-19 pandemic: A case study of China.

This paper examines and projects the water use and wastewater generation during and after the SARS-CoV-2 (COVID-19) in China, and discussed the water use/wastewater generation pattern changes among different sectors. Existing studies on the impact of pandemic spread-prevention measures on water consumption and wastewater treatment during the pandemic are reviewed. The water use and wastewater discharge in China through the COVID-19 period are then projected and analyzed using Multivariate Linear Regression. The projection is carried out for years 2019-2023 and covers an (estimated) full process of pre-pandemic, pandemic outbreak, and recovery phase and provides essential information for determining the complete phase impact of the COVID-19. Two scenarios, i.e. the recovery scenario and the business as usual scenario, are set to investigate the water use and wastewater generation characteristics after the pandemic. The results imply that in both scenarios, the water use in China shows a V-shaped trend from 2019 to 2023 and reached a low point in 2020 of 5,813✕108 m3. The wastewater discharge shows an increasing trend throughout the COVID period in both scenarios. The results are also compared with the water consumption and wastewater generation during the SARS-CoV-1 period. The implication for policymakers is the possible increase of water use and wastewater discharge in the post COVID period and the necessity to ensure the water supply and control of water pollution and wastewater discharge.

Industrial site water exchange network synthesis considering multiple quality constraints and water headers.

This work aims to extend the previous Pinch Analysis framework to the industrial site material recycling network with site headers synthesis from single quality to multiple qualities. The analysis provides guided resources management strategy in any eco-industrial park to reduce the reliance on raw resources that are extracted from the environment. The Pinch Point(s) are first identified for the overall network using the Material Recovery Pinch Diagram for all the qualities. The guideline for the cross-plant material sources transfer is then built upon the concept of the Pinch Point(s) for all the qualities to minimise the cross-plant source transfer or a number of connections. An iterative header targeting framework is then proposed to determine the flowrates and the qualities of the headers. Two case studies, which have single and multiple qualities Total Site water recycling network, are used to demonstrate the proposed framework, comparing results obtained using direct integration and centralised headers. The single quality case results in 4.1% lower fresh resource intake compared to without cross-transfer, while the multiple qualities case could have 5.3% lower fresh resources for two and three plants scenarios. This framework provides a proper analysis of the problem, which allows users to gain insights on the effective cross-plant source transfer schemes with headers constraint by resource qualities.

Clustering and optimising regional segregated resource allocation networks.

Policymakers and officials worldwide are making more stringent environmental norms and waste disposal policies to encourage industries to move towards cleaner production. One of the main challenges that industries face moving towards cleaner production is the adoption of different strategies for optimising their resource utilisation and waste reduction economically. This is particularly challenging for large-scale industries or a group of industrial plants located in an industrial region. This paper presents a novel approach to economic resource optimisation focussed mainly on large-scale industries, different industrial plants located in the vicinity of each other, or an industrial symbiosis network. In this work, a clustering algorithm is developed to segregate the given plants into different clusters based on the concept of load deficits and surpluses of each plant. The concept ideally allows only the plants with surpluses to send out their unused sources and plants with deficits to only receive external sources/resources. The clusters are formed based on the distances between plants, which in turn helps in saving transportation and communication costs. The clustered plants are then easy to optimise and manage for resource and cost optimality. The applicability of the proposed clustering algorithm is demonstrated using two case studies from the domain of water recycling networks containing multiple contaminants with detailed network design, highlighting the importance of clustering in an industrial symbiosis network. It is observed that directing the excess flows from one plant to other plants in the same cluster can save a considerable amount of fresh resources. It implies that in the broader aspect, the developed methodology can address the optimisation of economic resources and can aid in the better management of overall resources for a large-scale industrial symbiosis network.

A life cycle assessment of an enterprise's low-carbon emissions model: The Xinjiang Shihezi pig farm faecal treatment biogas project as a case study.

The requirement of carbon emission reduction promotes the continuous implementation and development of low carbon emission mode in typical high-carbon industry aquaculture, especially in the resourceful treatment of terminal waste. However, the previous studies usually focus on a single process or chain, the difference between the long-chain (LC) and automated integration (AI) in the overall environmental impact needs to be quantified and standardised. This paper intends to make a comparative study on two waste treatment biogas projects of aquaculture, a typical industry with high resource consumption and pollution emission in industry and agriculture, and a typical production mode case of aquaculture. The life cycle assessment method is adopted to analyse the environmental impact intensity, identify key link materials, and put forward targeted improvement and optimization schemes. The study found the LC system's comprehensive environmental impact (CEI) is smaller, which is 59.73% less than the AI system. Biogas slurry returning to the field can effectively avoid inorganic fertilizer input. The pretreatment and storage of feces are the key stages. The key substances are NH3 and nitrogen oxides. Suggestions were put forward to optimize the manure management process. In practical pig farms, the process of dry-cleaning manure pre-treatment, automatic fermentation gas production and final biogas slurry filtration drip irrigation should be promoted.

Industrial water network vulnerability analysis using dynamic inoperability input-output model.

Industrial parks provide opportunities for Process Integration among different enterprises. Inter-Plant Water Network Integration is an effective strategy for water conservation. However, increased interplant linkages can make the entire system vulnerable to cascading failures in case of loss of water flow in some plants. The potential indirect impact of water shortages on such integrated systems may not be evident without the use of appropriate models. This work defines inoperability as the fractional loss of water flow relative to normal operations. A comparison between the applicability of demand-driven versus supply-driven Inoperability Input-output Model (IIM) is conducted. Then, a Vulnerability Assessment Framework which integrates vulnerability indicators into the Dynamic Input-Output Model (DIIM) is developed to analyse failure propagation in water networks in an industrial park. The DIIM is then applied to simulate the cascading effects of disturbances. From a time perspective, the vulnerabilities of the industrial parks With Integrated Optimal Water Network (WWN) and Without Integrated Optimal Water Network (WOWN) are assessed considering robustness, adaptability, and recoverability as the indicators. The results indicate that supply-driven IIM is more suitable for cascading failure analysis of water networks. The average inoperability at 16% from supply-driven IIM is higher than that from demand-driven IIM. In the freshwater disturbance scenario, the dependence of the plant on freshwater is proportional to the rate of inoperability change, the time to reach a new equilibrium. In this study, the robustness of WWN is about fivefold that of WOWN, but the recovery rate is only one-sixth of the latter. This work can help identify system vulnerabilities and provide a scientific insight for the development of park-wide water management strategies.

Blockchain technology for agricultural supply chains during the COVID-19 pandemic: Benefits and cleaner solutions.

This study aims to investigate blockchain technology for agricultural supply chains during the COVID-19 pandemic. Benefits and solutions are identified for the smooth conduction of agricultural supply chains during COVID-19 using blockchain. This study uses interviews with agricultural companies operating in Pakistan. The findings discover the seven most commonly shared benefits of applying blockchain technology, four major challenges, and promising solutions. About 100% of the respondents mentioned blockchain as a solution for tracking the shipment during COVID-19, data retrieval and data management, product and transaction frauds, and an Inflexible international supply chain. Roughly 75% of the respondents mentioned the challenge of lack of data retrieval and data management and the Inflexible international supply chain in COVID-19 besides their solutions. This study can expand existing knowledge related to agricultural supply chains. The experiences shared in this study can serve as lessons for practitioners to adopt the blockchain technology for performing agricultural supply chain during pandemic situations such as COVID-19.

Energy, environmental, economic and social equity (4E) pressures of COVID-19 vaccination mismanagement: A global perspective.

Vaccination now offers a way to resolve the COVID-19 pandemic. However, it is critical to recognise the full energy, environmental, economic and social equity (4E) impacts of the vaccination life cycle. The full 4E impacts include the design and trials, order management, material preparation, manufacturing, cold chain logistics, low-temperature storage, crowd management and end-of-life waste management. A life cycle perspective is necessary for sustainable vaccination management because a prolonged immunisation campaign for COVID-19 is likely. The impacts are geographically dispersed across sectors and regions, creating real and virtual 4E footprints that occur at different timescales. Decision-makers in industry and governments have to act, unify, resolve, and work together to implement more sustainable COVID-19 vaccination management globally and locally to minimise the 4E footprints. Potential practices include using renewable energy in production, storage, transportation and waste treatment, using better product design for packaging, using the Internet of Things (IoT) and big data analytics for better logistics, using real-time database management for better tracking of deliveries and public vaccination programmes, and using coordination platforms for more equitable vaccine access. These practices raise global challenges but suggest solutions with a 4E perspective, which could mitigate the impacts of global vaccination campaigns and prepare sustainably for future pandemics and global warming.

Impacts of urban land morphology on PM2.5 concentration in the urban agglomerations of China.

Accurate understanding of the relationship between urban land morphology and the concentration of PM2.5 is essential for achieving high-quality development of urban agglomerations. Based on a mechanism framework of "Internal-External driving force", 19 Chinese urban agglomerations at different development levels were analysed using the geographically weighted regression model to evaluate the impacts of urban land morphology on PM2.5 concentrations in years 2000-2017. The results show: (1) The PM2.5 average concentrations of all 19 urban agglomerations continue to increase from 30 µg/m3 in 2000 to 52 µg/m3 in 2007 but decreased to 34 µg/m3 in 2017. The changes in PM2.5 concentrations vary for urban agglomerations at different development levels. Spatial differences in PM2.5 concentrations are significant, forming a pattern that decreases from the centre to the periphery regions; (2) The urban land morphology of the entire urban agglomeration areas has undergone significant changes. The fractal dimension index (from 4.150 to 2.731) and the compactness (from 0.647 to 0.635) showed a downward trend, while the shape indices (from 1.421 to 1.606) demonstrated an increasing trend. National-level urban agglomerations are more compact and more complex in shape, while more fragmented are regional and local urban agglomerations; (3) Different parameters of urban land morphology have varying effects on PM2.5 concentration varies and at different development levels of urban agglomerations. The combination of urban land morphology, socio-economic factors, and natural elements has a complex effect on PM2.5 concentrations. It can contribute to understanding the linkage between urban land morphology and PM2.5, providing references for future studies.

Urban and industrial symbiosis for circular economy: Total EcoSite Integration.

The paper presents an extension of Pinch Analysis and namely, Total Site Process Integration. It benefits from up to date developments and introduction of Total EcoSite Integration for urban and industrial symbiosis. An important development is Pinch Analysis for Solid Waste Integration which is a crucial step for the symbiosis in a circular economy. As the potential EcoSites are usually extensive and cover various units, a methodology based on clusters has been used. The solution has been supported by graphical tools using the analogy with already implemented extensions of Pinch Analysis. The results of a demonstration case study revealed the potential of the novel approach. The identified integrated design increased the energy recovered from the solid waste by 11.39 MWh/d and diverted 2 t/d of the waste from the landfill, benefiting both the urban and industrial site. The proposed approach is also capable of minimising the requirement of energy-intensive thermal drying for waste whenever the process allowed, subsequently offer a solution with lower environmental footprint and cost. For future work, a even more comprehensive case study can be conducted by considering the other forms of the waste, recovery process and drying approaches.

A Heat and Power Pinch for Process Integration targeting in hybrid energy systems.

Hybrid energy systems have been widely used for residential and industrial purposes. In this system, the total energy requirement of each unit can be met with heat and electricity. Pinch Analysis becomes a widely used tool for Process Integration, and using Pinch Analysis for Heat Integration is well-established. However, for the combined heat and power system, the theory and the corresponding tool deserve some more development. This paper extended the Pinch Analysis concept and proposed a Heat and Power Pinch Analysis to target the amount of heat that should be recovered from the hybrid energy system. Heat and Power Composite Curve (HPCC) is developed to visualise the total energy and the separated heat and power (electricity) requirement of a hybrid energy system in a working time period. The amount of outsourced electricity that should be purchased, and stored electricity at the startup period, and the extra electricity generated by the system at the end of the working period can be demonstrated. A case is studied to illustrate the steps of using this tool, two scenarios are discussed, and the targets are shown.

A review on plant-microbial interactions, functions, mechanisms and emerging trends in bioretention system to improve multi-contaminated stormwater treatment.

Management and treatment of multi-polluted stormwater in bioretention system have gained significant attraction recently. Besides nutrients, recent source appointment studies found elevated levels of Potentially toxic metal(loid)s (PTMs) and contaminants of emerging concern (CECs) in stormwater that highlighted many limitations in conventional media adsorption-based pollutant removal bioretention strategies. The substantial new studies include biological treatment approaches to strengthen pollutants degradation and adsorption capacity of bioretention. The knowledge on characteristics of plants and their corresponding mechanisms in various functions, e.g., rainwater interception, retention, infiltration, media clogging prevention, evapotranspiration and phytoremediation, is scattered. The microorganisms' role in facilitating vegetation and media, plant-microorganism interactions and relative performance over different functions in bioretention is still unreviewed. To uncover the underneath, it was summarised plant and microbial studies and their functionality in hydrogeochemical cycles in the bioretention system in this review, contributing to finding their interconnections and developing a more efficient bioretention system. Additionally, source characteristics of stormwater and fate of associated pollutants in the environment, the potential of genetical engineered plants, algae and fungi in bioretention system as well as performance assessment of plants and microorganisms in non-bioretention studies to propose the possible solution of un-addressed problems in bioretention system have been put forward in this review. The present review can be used as an imperative reference to enlighten the advantages of adopting multidisciplinary approaches for the environment sustainability and pollution control.

Total Site Heat Integration benefiting from geothermal energy for heating and cooling implementations.

Geothermal energy is a promising renewable energy source that has been developed by many countries in recent years. It can be utilised to meet various energy demand. This paper studies the performance of integrating geothermal energy in the Locally Integrated Energy Sector (LIES). The heating and cooling demand of various processes should be satisfied, and heat among processes should be recovered. This is done by using Grand Composite Curves and Total Site Profiles to visually illustrate how much load is required for utility systems. The geothermal utility system and steam utility system are compared. The integration plan for geothermal energy under different temperatures are studied. An illustrative case shows that by using this type of renewable energy under a specific and favourable condition, above 70% of steam utility load can be saved. The working cycle of using a geothermal utility system is studied by using the Time Slice model. The heat recovery plan for normal operation, mineral scaling, and cleaning periods are optimised. The minimum temperature for heat storage can also be identified.

Dilution rate of compost leachate from different biowaste for the fertigation of vegetables.

Compost leachate (CL) is often treated as sewage. Limited studies have characterised the use of CL for agriculture application due to the variation of nutrient range, potential pollutants and need for pretreatment before use. This paper reviewed the characteristics of CL in terms of its nutrients and physical characteristics from three types of biowastes, i.e. the organic portion of municipal solid waste (OP-MSW), animal manure and green waste. The nutrient range characterised are used to develop the dilution rate of the CL as fertigation water for three types of vegetables. The dilution rate of CL developed is based on the fertigation standards set by the Food and Agriculture Organization of the United Nations and Malaysia Standards. The results show that all CL contain high organic content and micronutrients, which exceeded the upper limits. For the fertigation of vegetables using the CL, based on the requirement of COD and micronutrients (Fe, Mn, Zn, Cu, Pb, Ni, Cd, Cr) of the vegetables, the CL from green waste required the lowest dilution rate (8-45 fold), followed by animal waste (33-65 fold) and the OP-MSW (193-1770 fold). The novel dilution range developed is vital to balance the essential nutrients in the CL while avoiding phototoxicity on plant and soil pollution. The dilution strategy developed is essential to support the conversion of CL as an organic liquid fertiliser for agricultural application.

Data analytics of social media publicity to enhance household waste management.

Household waste segregation and recycling is ranked at a high priority of the waste management hierarchy. Its management remains a great challenge due to the high dependency on social behaviours. The integration of Internet of Things (IoT) and subscription accounts on social media platforms related to household waste management could be an effective and environmentally friendly publicity approach than traditional publicity via posters and newspapers. However, there is a paucity of literature on measuring social media publicity in household waste management, which brings challenges for practitioners to characterise and improve this publicity pathway. In this study, under an integrated framework, data mining approaches are employed or extended for multidimensional publicity analytics using the data of online footprints of propagandist and users. A real-world case study based on a subscription account on the WeChat platform, Shanghai Green Account, is analysed to reveal useful insights for personalised improvements of household waste management. This study suggests that the current publicity related to household waste management leans towards propagandist-centred in both timing and topic dimensions. The identified timing, which has high user engagement, is 12:00-13:00 and 21:00-22:00 on Thursday. The overall relative publicity quality of historical posts is calculated as 0.95. Average user engagement under the macro policy in Shanghai was elevated by 138.5% from 2018 to 2019, during which the collections of biodegradable food waste and recyclable waste were elevated by 88.8% and 431.8%. Intelligent decision support by publicity analytics could enhance household waste management through effective communication.

Impacts of COVID-19 on energy demand and consumption: Challenges, lessons and emerging opportunities.

COVID-19 has caused great challenges to the energy industry. Potential new practices and social forms being facilitated by the pandemics are having impacts on energy demand and consumption. Spatial and temporal heterogeneities of impacts appear gradually due to the dynamics of pandemics and mitigation measures. This paper overviews the impacts and challenges of COVID-19 pandemics on energy demand and consumption and highlights energy-related lessons and emerging opportunities. The discussion on energy-related issues is divided into four main sections: emergency situation and its impacts, environmental impacts and stabilising energy demand, recovering energy demand, and lessons and emerging opportunities. The changes in energy requirements are compared and analysed from multiple perspectives according to available data and information. In general, although the overall energy demand declines, the spatial and temporal variations are complicated. The energy intensity has presented apparent changes, the extra energy for COVID-19 fighting is non-negligible for stabilising energy demand, and the energy recovery in different regions presents significant differences. A crucial issue has been to allocate and find energy-related emerging opportunities for the post pandemics. This study could offer a direction in opening new avenues for increasing energy efficiency and promoting energy saving.